TabFM

Google's tabular foundation model: zero-shot prediction on unseen tables via in-context learning, trained "entirely on hundreds of millions of synthetic datasets" generated from structural causal models — no real-world data. Alternating row/column-attention encoder feeding a 24-block causal ICL transformer; parameter count unstated. Beats tuned gradient-boosted trees on TabArena. Weights under the TabFM Non-Commercial License v1.0; code Apache-2.0. Extends the TabPFN line of prior-fitted tabular models to Google scale.